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clean up documents, changelog, readme
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84 changes: 47 additions & 37 deletions ChangeLog
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2023-11-14 Tao Liu <vladimir.liu@gmail.com>
2023-11-15 Tao Liu <vladimir.liu@gmail.com>
MACS 3.0.0

* New features in MACS3:

1) Speed/memory optimization. Use the cykhash to replace python
1) Call variants in peak regions directly from BAM files. The
function was originally developed under code name SAPPER. Now
SAPPER has been merged into MACS as the `callvar` command. It can
be used to call SNVs and small INDELs directly from alignment
files for ChIP-seq or ATAC-seq. We call `fermi-lite` to assemble
the DNA sequence at the enriched genomic regions (binding sites or
accessible DNA) and to refine the alignment when necessary. We
added `simde` as a submodule in order to support fermi-lite
library under non-x64 architectures.

2) HMMRATAC module is added as subcommand `hmmratac`. HMMRATAC is
a dedicated software to analyze ATAC-seq data. The basic idea
behind HMMRATAC is to digest ATAC-seq data according to the
fragment length of read pairs into four signal tracks: short
fragments, mono-nucleosomal fragments, di-nucleosomal fragments
and tri-nucleosomal fragments. Then integrate the four tracks
again using Hidden Markov Model to consider three hidden states:
open region, nucleosomal region, and background region. The
orginal paper was published in 2019 written in JAVA, by Evan
Tarbell. We implemented it in Python/Cython and optimize the whole
process using existing MACS functions and hmmlearn. Now it can run
much faster than the original JAVA version. Note: evaluation of
the peak calling results is still underway.

3) Speed/memory optimization. Use the cykhash to replace python
dictionary. Use buffer (10MB) to read and parse input file (not
available for BAM file parser). And many optimization tweaks. We
added memory monitoring to the runtime messages.

2) Call variants in peak regions directly from BAM files. The
function was originally developed under code name SAPPER. Now
SAPPER has been merged into MACS. Also, `simde` has been added as
a submodule in order to support fermi-lite library under non-x64
architectures.

3) HMMRATAC module is added. HMMRATAC is a dedicated software to
analyze ATAC-seq data. The basic idea behind HMMRATAC is to digest
ATAC-seq data according to the fragment length of read pairs into
four signal tracks: short fragments, mononucleosomal fragments,
di-nucleosomal fragments and tri-nucleosomal fragments. Then
integrate the four tracks again using Hidden Markov Model to
consider three hidden states: open region, nucleosomal region, and
background region. The orginal paper was published in 2019 written
in JAVA, by Evan Tarbell. We implemented it in Python/Cython and
optimize the whole process using existing MACS functions and
hmmlearn. Now it can run much faster than the original JAVA
version. Note: evaluation of the peak calling results is underway.
4) R wrappers for MACS -- MACSr for bioconductor.

4) Code cleanup. Reorganize source codes.
5) Code cleanup. Reorganize source codes.

5) Unit testing.

6) R wrappers for MACS -- MACSr
6) Unit testing.

7) Switch to Github Action for CI, support multi-arch testing
including x64, armv7, aarch64, s390x and ppc64le. We also test on
Mac OS 12.

8) MACS tag-shifting model has been refined. Now it will use a
8) MACS tag-shifting model has been refined. Now it will use a
naive peak calling approach to find ALL possible paired peaks at +
and - strand, then use all of them to calculate the
cross-correlation. (a related bug has been fix #442)
and - strand, then use all of them to calculate the
cross-correlation. (a related bug has been fix
[#442](https://github.com/macs3-project/MACS/issues/442))

9) BAI index and random access to BAM file now is supported. #449
And user can use original BAM file (instead of the subset of BAM
file as in SAPPER) in the `callvar` command.
9) BAI index and random access to BAM file now is
supported. [#449](https://github.com/macs3-project/MACS/issues/449).

10) Support of Python > 3.10 #497 #498
10) Support of Python > 3.10
[#498](https://github.com/macs3-project/MACS/issues/498)

11) The effective genome size parameters have been updated
according to deeptools. #508
according to
deeptools. [#508](https://github.com/macs3-project/MACS/issues/508)

12) Multiple updates regarding dependencies, anaconda built, CI/CD
process.

13) Cython support to ~0.29. Cython 3 is not supported yet.
13) Cython 3 is supported.

14) Documentations for each subcommand can be found under /docs

*Other*

* Other:
1) Missing header line while no peaks can be called #501 #502
1) Missing header line while no peaks can be called
[#501](https://github.com/macs3-project/MACS/issues/501)
[#502](https://github.com/macs3-project/MACS/issues/502)

2) Note: different numpy, scipy, sklearn may give slightly
different results for hmmratac results. The current standard
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79 changes: 42 additions & 37 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -27,37 +27,42 @@ applied to any "DNA enrichment assays" if the question to be asked is
simply: *where we can find significant reads coverage than the random
background*.

## Recent Changes for MACS (3.0.0)
## Changes for MACS (3.0.0)

1) Speed/memory optimization. Use the cykhash to replace python
1) Call variants in peak regions directly from BAM files. The
function was originally developed under code name SAPPER. Now
SAPPER has been merged into MACS as the `callvar` command. It can
be used to call SNVs and small INDELs directly from alignment
files for ChIP-seq or ATAC-seq. We call `fermi-lite` to assemble
the DNA sequence at the enriched genomic regions (binding sites or
accessible DNA) and to refine the alignment when necessary. We
added `simde` as a submodule in order to support fermi-lite
library under non-x64 architectures.

2) HMMRATAC module is added as subcommand `hmmratac`. HMMRATAC is a
dedicated software to analyze ATAC-seq data. The basic idea behind
HMMRATAC is to digest ATAC-seq data according to the fragment
length of read pairs into four signal tracks: short fragments,
mono-nucleosomal fragments, di-nucleosomal fragments and
tri-nucleosomal fragments. Then integrate the four tracks again
using Hidden Markov Model to consider three hidden states: open
region, nucleosomal region, and background region. The orginal
paper was published in 2019 written in JAVA, by Evan Tarbell. We
implemented it in Python/Cython and optimize the whole process
using existing MACS functions and hmmlearn. Now it can run much
faster than the original JAVA version. Note: evaluation of the
peak calling results is still underway.

3) Speed/memory optimization. Use the cykhash to replace python
dictionary. Use buffer (10MB) to read and parse input file (not
available for BAM file parser). And many optimization tweaks. We
added memory monitoring to the runtime messages.

2) Call variants in peak regions directly from BAM files. The
function was originally developed under code name SAPPER. Now
SAPPER has been merged into MACS. Also, `simde` has been added as
a submodule in order to support fermi-lite library under non-x64
architectures.

3) HMMRATAC module is added. HMMRATAC is a dedicated software to
analyze ATAC-seq data. The basic idea behind HMMRATAC is to digest
ATAC-seq data according to the fragment length of read pairs into
four signal tracks: short fragments, mononucleosomal fragments,
di-nucleosomal fragments and tri-nucleosomal fragments. Then
integrate the four tracks again using Hidden Markov Model to
consider three hidden states: open region, nucleosomal region, and
background region. The orginal paper was published in 2019 written
in JAVA, by Evan Tarbell. We implemented it in Python/Cython and
optimize the whole process using existing MACS functions and
hmmlearn. Now it can run much faster than the original JAVA
version. Note: evaluation of the peak calling results is underway.
4) R wrappers for MACS -- MACSr for bioconductor.

4) Code cleanup. Reorganize source codes.
5) Code cleanup. Reorganize source codes.

5) Unit testing.

6) R wrappers for MACS -- MACSr
6) Unit testing.

7) Switch to Github Action for CI, support multi-arch testing
including x64, armv7, aarch64, s390x and ppc64le. We also test on
Expand All @@ -70,9 +75,7 @@ background*.
[#442](https://github.com/macs3-project/MACS/issues/442))

9) BAI index and random access to BAM file now is
supported. [#449](https://github.com/macs3-project/MACS/issues/449)
And user can use original BAM file (instead of the subset of BAM
file as in SAPPER) in the `callvar` command.
supported. [#449](https://github.com/macs3-project/MACS/issues/449).

10) Support of Python > 3.10 [#498](https://github.com/macs3-project/MACS/issues/498)

Expand All @@ -82,7 +85,9 @@ background*.
12) Multiple updates regarding dependencies, anaconda built, CI/CD
process.

13) Cython 3 is supported yet.
13) Cython 3 is supported.

14) Documentations for each subcommand can be found under /docs

*Other*

Expand Down Expand Up @@ -140,14 +145,14 @@ of the subcommands.
Subcommand | Description
-----------|----------
[`callpeak`](./docs/callpeak.md) | Main MACS3 Function to call peaks from alignment results.
[`bdgpeakcall`](./docs/bdgpeakcall.md) | Call peaks from bedGraph output.
[`bdgbroadcall`](./docs/bdgbroadcall.md) | Call broad peaks from bedGraph output.
[`bdgpeakcall`](./docs/bdgpeakcall.md) | Call peaks from bedGraph file.
[`bdgbroadcall`](./docs/bdgbroadcall.md) | Call nested broad peaks from bedGraph file.
[`bdgcmp`](./docs/bdgcmp.md) | Comparing two signal tracks in bedGraph format.
[`bdgopt`](./docs/bdgopt.md) | Operate the score column of bedGraph file.
[`cmbreps`](./docs/cmbreps.md) | Combine BEDGraphs of scores from replicates.
[`cmbreps`](./docs/cmbreps.md) | Combine bedGraph files of scores from replicates.
[`bdgdiff`](./docs/bdgdiff.md) | Differential peak detection based on paired four bedGraph files.
[`filterdup`](./docs/filterdup.md) | Remove duplicate reads, then save in BED/BEDPE format file.
[`predictd`](./docs/predictd.md) | Predict d or fragment size from alignment results.
[`predictd`](./docs/predictd.md) | Predict d or fragment size from alignment results. In case of PE data, report the average insertion/fragment size from all pairs.
[`pileup`](./docs/pileup.md) | Pileup aligned reads (single-end) or fragments (paired-end)
[`randsample`](./docs/randsample.md) | Randomly choose a number/percentage of total reads, then save in BED/BEDPE format file.
[`refinepeak`](./docs/refinepeak.md) | Take raw reads alignment, refine peak summits.
Expand All @@ -161,11 +166,11 @@ from users.

## Contribute

Please read our [CODE OF CONDUCT](./CODE_OF_CONDUCT.md) and
[How to contribute](./CONTRIBUTING.md) documents. If you have any
questions, suggestion/ideas, or just want to have conversions with
developers and other users in the community, we recommand you use the
[MACS Discussions](https://github.com/macs3-project/MACS/discussions)
Please read our [CODE OF CONDUCT](./CODE_OF_CONDUCT.md) and [How to
contribute](./CONTRIBUTING.md) documents. If you have any questions,
suggestion/ideas, or just want to have conversions with developers and
other users in the community, we recommend using the [MACS
Discussions](https://github.com/macs3-project/MACS/discussions)
instead of posting to our
[Issues](https://github.com/macs3-project/MACS/issues) page.

Expand Down
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